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510(k) Data Aggregation
(220 days)
Advanced MyHip Planner
The MyHip Planner software is intended for image processing and preoperative planning of acetabular cup and femoral stem positioning for Total Hip Arthroplasty (THA). The user is assisted in producing a preoperative plan, making decisions based on the leg offsets, the patient's potential impingement and, optionally, the spino-pelvic interaction. Through the software, the user can request 3D Printed Patient Specific Bone Models not intended for dragnostic use, but only intended for a physical representation of the 3D anatomical models visualized in the software. The 3D Printed Patient Specific Bone Models are provided non-sterile.
The MyHip Planner is a software whose output is a patient-specific preoperative plan based on CT scans and aimed at evaluating the effects of different device choices and positioning options on the patient's hip joint biomechanics in terms of leg length and offset. It is intended to be used in Primary Hip Arthroplasty and it is compatible with Windows and Mac OS operating system. The subject Advanced version of the MyHip Planner additionally allows to evaluate patient's spinopelvic deformities and pelvic tilt starting from preoperative X-ray images, to help the surgeon to understand the implications of spinopelvic mobility on THA stability and optimize implant components orientation. Through the software, the user can request non-sterile 3D Printed Patient Specific Bone Models intended to be used as an additional visual reference of the patients' specific anatomy.
The Medacta International S.A. Advanced MyHip Planner (K221725) is a software intended for image processing and preoperative planning of acetabular cup and femoral stem positioning for Total Hip Arthroplasty (THA). The software assists users in producing a preoperative plan, making decisions based on leg offsets, potential impingement, and optionally, spino-pelvic interaction. It also allows users to request 3D Printed Patient Specific Bone Models (non-sterile, not for diagnostic use, but for physical representation of 3D anatomical models).
Here's an analysis of the acceptance criteria and study data provided:
1. Table of Acceptance Criteria and Reported Device Performance
The provided document does not explicitly present a table of acceptance criteria for specific performance metrics (e.g., accuracy, precision) of the Advanced MyHip Planner software. However, it states that "Software verification and validation including segmentation validation" was conducted, and "[n]o statistical divergence between the algorithm and the manual segmentation has been revealed by an analysis of the automatic segmentation and landmark picking performance on a two-sided students t-distribution."
Based on this, an inferred table might look like this, with the understanding that specific numerical acceptance criteria (e.g., within X mm or degrees of ground truth) are not explicitly detailed:
| Acceptance Criteria (Inferred) | Reported Device Performance |
|---|---|
| Segmentation Accuracy: Robust and accurate automatic segmentation of anatomical structures relevant for THA planning, spino-pelvic evaluation, and 3D bone model generation. | "No statistical divergence between the algorithm and the manual segmentation has been revealed by an analysis of the automatic segmentation and landmark picking performance on a two-sided students t-distribution." This suggests that the automated segmentation and landmark identification are statistically comparable to manual methods. |
| Landmark Picking Accuracy: Accurate automatic identification of anatomical landmarks crucial for preoperative planning measurements (cup/stem positioning, ROM, spino-pelvic evaluation). | "No statistical divergence between the algorithm and the manual segmentation has been revealed by an analysis of the automatic segmentation and landmark picking performance on a two-sided students t-distribution." This indicates the automated landmark picking is statistically comparable to manual methods. |
| Functionality: Correct operation of all software features, including image upload, segmentation, planning tools, spino-pelvic evaluation, and 3D bone model request. | "Based on the risk analysis, verification activities were conducted to written protocols." This typically implies testing of all functional requirements. |
2. Sample Size Used for the Test Set and Data Provenance
The document does not explicitly state the sample size used for the test set. It mentions "an analysis of the automatic segmentation and landmark picking performance," but the number of cases or images included in this analysis is not provided.
The data provenance (e.g., country of origin, retrospective or prospective) for the test set is also not specified.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and the Qualifications of Those Experts
The document refers to "manual segmentation" as a comparison point for the algorithm's performance. However, it does not specify the number of experts who performed this manual segmentation or landmark picking, nor does it explicitly detail their qualifications (e.g., radiologist with X years of experience, orthopedic surgeon).
4. Adjudication Method for the Test Set
The document refers to a "two-sided students t-distribution" analysis to compare algorithm performance with manual segmentation. This implies a statistical comparison rather than a formal adjudication process involving multiple human readers to resolve discrepancies. Therefore, an explicit adjudication method like 2+1 or 3+1 is not mentioned. The "manual segmentation" serves as the reference, suggesting a single ground truth from a human expert or a pre-established "gold standard" of manual interaction.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done
The document explicitly states: "No clinical studies were conducted." Therefore, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study to evaluate human reader improvement with AI assistance was not performed.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) was Done
The performance data section mentions "Software verification and validation including segmentation validation" and "an analysis of the automatic segmentation and landmark picking performance." This indicates that standalone performance evaluation (algorithm only) of the segmentation and landmark picking functionalities was performed. The comparison was against "manual segmentation" which serves as the independent reference for the algorithm's output.
7. The Type of Ground Truth Used
The ground truth for the verification and validation activities, specifically for segmentation and landmark picking, appears to be expert consensus through "manual segmentation" and "manual landmark picking." The document uses these manual methods as the reference against which the algorithm's performance was compared. There is no mention of pathology or outcomes data being used for ground truth for these specific performance evaluations.
8. The Sample Size for the Training Set
The document does not specify the sample size used for the training set for the Advanced MyHip Planner software.
9. How the Ground Truth for the Training Set Was Established
The document does not describe how the ground truth for the training set was established. While it mentions comparison to manual segmentation for validation, it does not elaborate on the process or sources of ground truth used during the development and training phases of the algorithm.
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